338 machine-learning-"https:" "https:" "https:" "RAEGE Az" positions at KINGS COLLEGE LONDON
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are seeking a postdoctoral research associate to lead an innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a
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environment for the pursuit of cutting-edge cardiovascular and metabolic research (https://www.kcl.ac.uk/scms ). We study the fundamental molecular, cellular, and physiological processes that underly normal and
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approach, combining both traditional teaching methods with modern, project-based learning, catering for the needs of our students and the industries in which they will work. As a new department we have
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system may hold clues to how psychosis and other psychiatric disorders are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine
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(Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and
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to creating social and economic value for both business and society. We offer a wide selection of undergraduate and postgraduate programmes (see https://www.kcl.ac.uk/business), with sustainability at the heart
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on the King’s website: Department of Political Economy: http://www.kcl.ac.uk/sspp/departments/politicaleconomy/index.aspx School of Politics and Economics: http://www.kcl.ac.uk/sspp/schools/politics-economics
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information about the Department, School and Faculty can be found on the King’s website: Department of Political Economy: http://www.kcl.ac.uk/sspp/departments/politicaleconomy/index.aspx School of Politics
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communication skills Desirable criteria Experience in application of machine learning to metamaterials modelling Experience in modelling molecular interactions Experience in modelling of mass transport
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metabolism Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and